דרושים » AI » חברת one טכנולוגיות מגייסת מטמיע /ת AI לגוף מוביל במרכז

Requirements:
3+ years of leadership experience as a team lead, tech lead, or engineering manager.
3+ years of hands-on experience in AI inference, production ML infrastructure, model serving, or AI runtime platforms.
Strong experience with production inference technologies such as Triton, vLLM, CUDA, Kubernetes, Docker, PyTorch, ONNX, TensorRT, or similar.
3+ years of experience with Go, or strong experience with a similar high-performance backend language such as C++, Rust, or Java.
Experience with performance optimization, scalability, observability, and SLO-driven production ownership.
Strong system design skills, especially around distributed systems, performance, reliability, and production infrastructure.
Advantages:
Experience with GPU optimization, GPU scheduling, GPU resource efficiency, quantization, runtime acceleration, or large-scale model serving.

Requirements:
WHAT YOU WILL BRING
5+ years of professional experience as a research scientist, applied scientist, or algorithms/ML engineer.
Ph.D. or Masters degree in computer science, machine learning, data science, statistics, or a related field.
Expert-level proficiency in PyTorch and deep learning training and inference optimization.
Hands-on experience training, fine-tuning, evaluating, or optimizing large-scale LLMs in research or production environments.
Strong Python programming skills and experience writing production-grade ML code.
Experience working with large-scale data and ML infrastructure.


NICE TO HAVE
Experience applying AI/ML to cybersecurity, including threat detection, incident response, log analysis, or related problems.
Experience with reinforcement learning or preference optimization for LLMs.
A track record of research publications, open-source contributions, or other technical work demonstrating research depth.

Requirements:
5+ years of experience as a Research Scientist or Algorithm Developer within world-class AI labs or high-growth GenAI startups
Ph.D. or Masters degree with honors in computer science, data science, statistics, or a highly quantitative field from a top-tier institution
Expert-level proficiency in PyTorch and deep learning training/inference optimization
Hands-on experience training, fine-tuning, or optimizing large-scale LLMs in research or production environments
Advanced programming skills in Python and/or C/C++ with experience in production-grade code and big data infrastructure
A portfolio of peer-reviewed publications in top-tier AI/ML venues or granted patents in advanced machine learning systems.

Requirements:
Deep, hands-on application security experience at an engineering level: someone who sits with dev teams, understands development processes from the inside, and reviews code and architectures as a peer (Must)
At least 1 year of dedicated, immersive work in AI security: research, experimentation, or offensive engagements targeting AI/ML systems (Must)
Offensive security capabilities with a focus on AI-specific attack vectors (Must)
Strong understanding of AI/ML technologies, including LLMs, agentic systems, and common AI application architectures
Development skills: comfortable reading and writing code, building tools, and understanding codebases
Excellent communication skills and comfort working directly with enterprise customers
Fluent English
Nice to have:
Published research or public talks on AI security topics
Experience with traditional penetration testing or red teaming
Background in building or deploying AI/ML systems from the development side.

Requirements:
MSc or PhD in Computer Science, Mathematics, Physics, Electrical Engineering, or a closely related field.
Proficiency in Python.
Strong theoretical background in machine learning and deep learning principles.
Solid understanding of NLP concepts and relevant linguistic principles (co-reference, natural language inference, grammatical relations, and similar).
Experience using statistics and information theory to evaluate AI models and conduct EDA.
4+ years of experience conducting NLP research with deep learning models and frameworks (PyTorch, TensorFlow, and similar).
Experience shipping AI systems from research to production.
Experience with conversational AI agents is a big plus.
Publications at top-tier conferences (ACL, EMNLP, NeurIPS, ICML, CVPR) are a plus.

Requirements:
5+ years of experience in data analysis, product analytics, or a similar analytical role, including senior or lead-level scope.
Strong SQL skills and proven experience working with large datasets.
Proficiency with Python (or similar) for data analysis and automation.
Hands-on experience with GenAI tools, LLMs, and AI agents, and a good understanding of how they behave.
Experience analyzing the output and quality of AI or ML-driven products.
A track record of translating data into insights that influence product decisions and deliver measurable impact.
Ability to communicate findings clearly to technical and non-technical stakeholders, and to collaborate with and influence cross-functional teams.
Preferred
Experience measuring the quality or performance of AI systems.
Experience at a fast-growing product or SaaS company.
Familiarity with the security domain - threat modeling, application security, or related fields.
Experience mentoring analysts or setting analytical standards on a team.

Requirements:
who you are and what youve done
3+ years of experience in designing and implementing ai/ml algorithms, with a strong focus on signal processing
master's degree in Computer Science, electrical engineering, or a related field, or equivalent experience
proven experience working across the full ml lifecycle - from data acquisition and model training to production implementation and ongoing product iteration
moves fast, with strong engineering instincts, able to choose the right level of complexity to drive real-world impact
a get things done attitude with a strong sense of ownership
a team player with excellent communication and collaboration skills; able to convey complex ideas clearly to technical and non-technical partners
exceptional analytical and problem-solving skills
a fast learner, willing to try things out of your comfort zone
experience in speech, audio, or music-related domains - advantage

Requirements:
BSc in a relevant field (CS, EE, BioMed) - a must
Experience in Python development - a must
Vision AI models hands on experience - a must
Prior employment / MSc in a relevant field - an advantage
Experience in academic publishing - an advantage.

Requirements:
Academic background: B.Sc. in an engineering or quantitative scientific field, with coursework or focus in data science, machine learning, or information systems (or equivalent experience).
Experience: 5+ years of hands-on experience in applied AI research, data engineering, data science, or applied ML - ideally with security-related domains.
Strong Python & Data Pipelines: Proven ability to build robust pipelines that handle large-scale, real-world data.
LLM Systems in Production: Experience building and shipping real product features powered by LLMs, taking solutions from prototype to production, owning reliability through evaluation and monitoring.
Cyber Security Domain Knowledge: Familiarity with core security concepts, including asset inventory and context, vulnerability management and risk prioritization, exposure/attack-surface analysis, network and traffic analysis, and practical remediation workflows in collaboration with security teams.
Experiments & Workflow Design: Experience designing and running experiments and building reproducible end-to-end data workflows to validate new product features and iterate based on measurable results.
Problem Solving Skills: Strong analytical and critical-thinking skills, with the ability to break down ambiguous problems, apply sound algorithmic reasoning, and develop creative, pragmatic solutions.
Startup Mindset: High ownership, strong collaboration, and the ability to execute quickly and effectively in a fast-paced, evolving environment.
Advantage
Experience working with security datasets and real-world enterprise environments.
Experience building structured extraction and normalization systems using LLMs.
Strong product intuition: ability to turn AI capabilities into features users trust and rely on.
Experience designing AI monitoring systems (quality drift, and evaluation pipelines).